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Data SourcesMISR Level 1B2 Terrain Radiances; MISR Level 2 Aerosol Parameters; MODIS/AQUA AEROSOL 5-MIN L2 SWATH 10KM; MODIS 14 Land Cover Product (LandCover 1: IGBP Classification; aggregated by authors); Shuttle Radar Topography Mission (SRTM) elevation data.References Diner, D., Beckert, J., Reilly, T., Bruegge, C., Conel, J., Kahn, R., Martonchik, J., Ackerman, T., Davies, R., Gerstl, S., Gordon, H., Müller, J.-P., Mynei, R., Seller, R.,Pinty, B. and Verstraete, M. (1998). Multi-angle Imaging SpectroRadiometer (MISR) description and experiment overview. IEEE Transactions on Geoscience andRemote Sensing, 34, 4, 1072-1087.Houghton, J.T., Ding, Y., Griggs, D.J., Nouguer, M., van derLinden, P.J., Dai, X., Maskell, K., and Johnson, C.A. (2001). Climate change 2001: the scientific basis.The third assessment report of Working Group I of the Intergovernmental Panel on Climate Change (IPCC).”Technical report, World Meteorological Organizationand the United Nations Environment Programme, Geneva, Switzerland.Justice, C.O., Kendall, J.D., Dowyt, P.R., and Scholes, R.J. (2002). The MODIS fire products. Remote Sensing of Environment, 83, 244-262.Acknowledgements This research was funded by NASA Research Opportunities for Space and Earth Science (ROSES-2005) Land-Cover/Land-Use Change Program Award #NNG06GD31G. Thanks to Jeff Fox and John Vogler at the East-West Center for ancillary data.Research Objectives We propose a process-based statistical framework to model the relationship between biomass burning, aerosols andatmospheric circulation.We hypothesize that (1) the associations between local biomass burning events and regional aerosol patterns can beidentified by modeling the joint behavior of this system using aspatio-temporal statistical model with a covariance structurethat is a function of “atmospheric distance”; i.e., a distance metric that respects the circulatory patterns in the atmosphere;and (2) the relative effect of fire events can be identified by statistically examining the correspondence of these eventscompared to an observed underlying structure of carbonaceous aerosols also influenced by other activities such as industrialpollution.The proposed research has four specific objectives. These are:•To develop a hierarchical Bayesian framework to study the association between biomass burning and regional carbonaceousaerosol concentrations that incorporates a process-based description of aerosol transport over space and time;•To quantify explicitly the uncertaintyinvolved in the relationship between biomass burning and regional aerosols, givenavailable data and the nature of complex, circulatory atmospheric transport patterns;•To contribute to the understanding of the implications of current land-use changesin Southeast Asia given the measuredeffects of biomass burning in the last 5 years on regional aerosol concentrations; and•To conduct scenario and sensitivity analysesat a regional level that advance the understanding of the implications ofbiomass burning.Methods The key contribution of our research will be to develop a comprehensive statistical framework for analyzing the associationbetween fire occurrences, biomass burning and the resulting spatial-temporal distribution of carbonaceous aerosols.A process-based hierarchical Bayesian model allows us to integrate:•Estimates from remotely-sensed data on aerosol distributions and fire occurrences;•Ancillary data: land cover, rainfall, population density, and topography; and•Numerical weather simulations describing atmospheric transport processes from which to identify the space-timecovariance across pixels as a function of atmospheric distance.Model components•MODIS product “Fire and Thermal Anomalies”: the center point of a 1km resolution pixel where a fire has occurred (Justiceet al. , 2002)•MISR products for aerosol composition: 17.6 km resolution optical depth, size and shape of aerosols, Angstrom componentand single-scattering albedo (Diner et al. 1998)•Model for Ozone And Related chemical Tracers (MOZART): atmospheric transport model, in conjunction with colleagues atthe National Center for Atmospheric Research (NCAR)MotivationMuch research to date regarding the environmental consequences of land-cover/land-usechange (LCLUC) has focused on the relationship between LCLUC andthe carbon cycle(for a summary, see Houghton et al., [2004]). One component of the LCLUC/carbon cyclerelationship that is not well understood is the process by whichLCLUC affects aerosoldistributions. The burning of biomass releases significant amounts of carbonaceousaerosols which may have negative human health impacts and could affect the radiationbudget and climate, both directly and indirectly.Due to the spatial and temporal variability of atmospheric transport patterns, local LCLUCcan result in changes in regional aerosol distributions. More precise knowledge regardingthe association between biomass burning and aerosols is needed in order to assess theimpact of local LCLUC events on regional aerosol concentrations.In this research, we will explore the relative effects of biomass burning (BB) in mainlandSoutheast Asia on the levels of carbonaceous aerosols within theregion, directlyaccounting for the spatial structure of the biomass burning-aerosol relationship given airtransport patterns.Project Outcomes and Deliverables The Bayesian hierarchical statistical framework will allow us toaddress thefollowing:•The identification of the emissions sources driving regional aerosol patterns (i.e.,the relative contribution of varying anthropogenic processes);•Assessment of the likely consequences of future LCLUC; and•The determination of future aerosol patterns under a variety of differentscenarios.Biomass-burning aerosols measurements and classification schemesWith a successfully fitted model, we can derive:•Estimates of the total contribution of biomass-burning aerosols from each fire tothe spatial structure of pollution aerosols;•The total amount of increase in biomass-burning aerosols associated with eachland cover class; and•The spatial-temporal properties of pollution within the study regionScenario buildingWe will employ the statistical model as a simulator to forecast•The spatial distribution of biomass-burning aerosols over time; and•The likely changes in this distribution effected by policy changes.Finally, we will develop a set of visualization toolsto enable a user to explorethese relationships by selecting model input, particular scenarios of interest, anddisplay model output.ProgressDeveloping Java-based applications to search, retrieve, modify and displayMODIS and MISR data, as an initial step toward an interactive web-basedapplication to support regional scale studies; andVisualization and exploratory data analysis of the associations between fires,elevation, land cover, and aerosols.Figure 1. Study area with fire occurrences and aerosol optical depth,January 30, 2004Exploring Land-Cover/Land-Use Change and Regional Aerosol Composition and Concentration inMainland Southeast AsiaN. Xiao1, D.K. Munroe1, C.A. Calder2, T. Shi2, C.Q. Lam2, D. Li1, S. Wolfinbarger11Department of Geography;2Department of Statistics; The Ohio State University, Columbus, OHFigure 2. Trend of associations between fires and aerosolconcentration. (a) optical depth; (b) aerosol fractions.(a)(b)(a)(b)